---
title: "Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    source: embed
---

```{r setup, include = FALSE}
# Load required libraries for the assignment

library(tidyverse)
library(p8105.datasets)
library(plotly)
library(flexdashboard)
```

```{r, include = FALSE}
# Load ny_noaa dataset, wrangle data, and reduce the n to a random sample of 5,000 weather observations

noaa_df = ny_noaa %>%
  janitor::clean_names() %>%
  separate(date, into = c("year", "month", "day"), sep = '-') %>%
  mutate(month = as.numeric(month),
         year = as.factor(year),
         month = month.abb[month],
         month = factor(month, levels = month.abb),
         tmax = as.numeric(tmax),
         tmin = as.numeric(tmin),
         prcp = as.numeric(prcp),
         snow = as.numeric(snow),
         prcp2 = prcp/10,
         tmax2 = tmax/10,
         tmin2 = tmin/10) %>% 
  filter(
    year %in% 2000:2010,
   !is.na(tmax),
   !is.na(tmin),
   !is.na(prcp),
   !is.na(snow)) %>% 
  sample_n(5000)
```

## Temperature

### Year-long maximum temperature

```{r}
max_temp = noaa_df %>%
  mutate(text_label = str_c("Tmax: ºC", tmax2, "\nTmin: ºC", tmin2),
         ) %>% 
  plot_ly(
    x = ~month, y = ~tmax2, type = "scatter", mode = "markers",
    color = ~id, text = ~text_label, alpha = 0.5, colors = "viridis")

max_temp
```

## Weather Events {.tabset .tabset-fade}

### Precipitation

Count of days with rain over time.

```{r}

```

### Snow

Snow distribution over time.

```{r}
```